Publicatii recente
Publicatii recente
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Feature Selection Based on a Decision Tree Genetic Algorithm (2023)
Abstract The feature selection problem has become a key undertaking within machine learning. For classification problems, it is known to reduce the computational complexity of parameter estimation, but also it […]
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Railway Switch Classification Using Deep Neural Networks (2023)
Abstract Railway switches represent the mechanism which slightly adjusts the rail blades at the intersection of two rail tracks in order to allow trains to exchange their routes. Ensuring that […]
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A Game Theoretic Based K-Nearest Neighbor Approach for Binary Classification (2023)
Abstract K-nearest neighbor is one of the simplest and most intuitive binary classification methods providing robust results on a wide range of data. However, classification results can be improved by […]
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A Light, 3D UNet-based Architecture for Fully Automatic Segmentation of Prostate Lesions from T2-MRI Images. (2023)
Abstract INTRODUCTION Prostate magnetic resonance imaging (MRI) has been recently integrated into the pathway of diagnosis of prostate cancer (PCa). However, the lack of an optimal contrast-to-noise ratio hinders automatic […]
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Fully automated bladder tumor segmentation from T2 MRI images using 3D U-Net algorithm (2023)
Abstract Introduction Bladder magnetic resonance imaging (MRI) has been recently integrated in the diagnosis pathway of bladder cancer. However, automatic recognition of suspicious lesions is still challenging. Thus, development of […]
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Generalizing an Improved GrowCut Algorithm for Mammography Lesion Detection (2023)
Abstract In the past five years, 7.8 million women were diagnosed with breast cancer. Breast cancer is curable if it is discovered in early stages. Therefore, mammography screening is essential. […]
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Image Reconstruction Using Cellular Automata and Neural Networks (2023)
Abstract Combining cellular automata (CA) with convolutional neural networks (CNN) has been overtime an important topic of scientific interest in the field of computer vision. This has been due to […]
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Towards an Unsupervised GrowCut Algorithm for Mammography Segmentation (2023)
Abstract Breast cancer is the most frequent type of malignancy in women, with 2.3 million diagnostics only in 2020. However, as a consequence of early diagnosis and appropriate treatment, more […]
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Breast Cancer Images Segmentation using Fuzzy Cellular Automaton (2023)
Abstract Breast cancer is the most common type of cancer found in women. One of the most effiective methods for early identification of breast cancer is the mammogram. Numerous computer-aided […]
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Towards an Improved Unsupervised Graph-Based MRI Brain Segmentation Method (2023)
Abstract Brain disorders are becoming more prevalent, and accurate brain segmentation is a vital component of identifying the appropriate treatment. This study introduces an enhanced graph-based image segmentation technique. The […]
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